Simplified AI Assistant Project - Chat Interface Developer Roles
Dev 1: Backend (FastAPI + LangChain integration) Dev 2: Frontend (Streamlit Chat UI) + GitHub Setup Dev 3: Prompt Engineering + Documentation + Conversation Flow
Day 1: Setup & Foundation Dev 1 (Backend):
Set up FastAPI project structure Install dependencies (fastapi, langchain, uvicorn) Create basic API with /chat endpoint for conversation
Dev 2 (Frontend + GitHub):
Create GitHub repo with branches (main, dev, prompt-design, ui, api-integration) Set up Kanban board on GitHub Projects Create Streamlit project with st.chat_message and st.chat_input
Dev 3 (Prompts + Docs):
Design conversational flow for each feature:
Bot asks questions to gather info User responds naturally
Create initial system prompts for chat assistant Define conversation stages (greeting → questions → generation)
Day 2: Core Development Dev 1 (Backend):
Implement LangChain chat setup with memory/context Create /chat endpoint that:
Receives user messages Maintains conversation history Returns AI responses
Add session management for conversations
Dev 2 (Frontend):
Build chat interface with Streamlit:
Message history display Chat input box User/Assistant message styling
Implement conversation state management Add "Start New Conversation" button
Dev 3 (Prompts + Flow):
Design conversational prompts:
Bio flow: "Hi! I'll help you create a bio. What's your name?" → "What are your key skills?" → etc. Project flow: "Let's create a project summary! What's the project name?" → "What technologies did you use?" → etc. Reflection flow: "I'll help you write a learning reflection. What topic did you learn about?" → etc.
Define when bot should ask follow-up questions vs. generate final output
Day 3: Integration & Conversation Logic Dev 1 (Backend):
Integrate Dev 3's conversational prompts Add logic to detect when to:
Ask follow-up questions Generate final output Offer to start new topic
Implement conversation context tracking
Dev 2 (Frontend):
Connect chat UI to backend /chat endpoint Display typing indicators during API calls Add buttons for quick actions:
"Generate Bio" "Summarize Project" "Write Reflection"
Implement copy-to-clipboard for final outputs
Dev 3 (Integration):
Work with Dev 1 on conversation state management Test conversation flows end-to-end Refine prompts based on testing Create conversation scripts/examples
Day 4: Polish & Features Dev 1 (Backend):
Add ability to regenerate responses Implement conversation export functionality Add error handling for failed responses Optimize response time
Dev 2 (Frontend):
Add sidebar with:
Conversation history Quick action buttons Examples section
Improve chat UI styling Add message timestamps Implement scroll-to-bottom on new messages
Dev 3 (UX + Docs):
Add welcome message with instructions Create example conversations for each feature Add helpful hints in chat (e.g., "Tip: Be specific about your skills") Write user guide documentation Test conversation flows with edge cases
Day 5: Final Polish & Demo Dev 1 (Backend):
Final testing and optimization Code cleanup Merge branches
Dev 2 (Frontend):
Final UI polish and styling Add branding/logo Ensure responsive design Prepare deployment
Dev 3 (Documentation):
Complete README.md with:
Setup instructions How to use the chat interface Example conversations
Document prompt engineering approach Create demo video/presentation Final end-to-end testing
Jira Board - 15 Cards Epic: Project Setup (Day 1)
[Dev 2] Create GitHub repo, branches, and Kanban board [Dev 1] Set up FastAPI with /chat endpoint structure [Dev 2] Build basic Streamlit chat interface [Dev 3] Design conversational flows for all 3 features
Epic: Backend Development (Day 2-3)
[Dev 1] Implement LangChain chat with conversation memory [Dev 1] Add session management and context tracking [Dev 1] Integrate conversational prompts and generation logic
Epic: Frontend Development (Day 2-3)
[Dev 2] Build chat UI with message history and input [Dev 2] Add quick action buttons and navigation [Dev 2] Connect frontend to backend chat API
Epic: Conversation Design (Day 2-3)
[Dev 3] Create system prompts for bio, summary, and reflection [Dev 3] Test and refine conversation flows
Epic: Polish & Features (Day 4)
[Dev 1 + Dev 2] Add regenerate, export, and UI enhancements [Dev 3] Add examples, welcome message, and user guidance
Epic: Documentation & Demo (Day 5)
[Dev 3] Complete documentation and demo preparation
Chat Flow Example
Bio Generation Conversation:
🤖 Assistant: Hi! I'm your AI assistant. I can help you create:
• Professional bios
• Project summaries
• Learning reflections
What would you like to create today?
👤 User: I need a professional bio
🤖 Assistant: Great! I'll help you create a compelling bio. Let's start with your name - what should I call you?
👤 User: John Doe
🤖 Assistant: Nice to meet you, John! What are your main skills or areas of expertise?
👤 User: Python, machine learning, data analysis
🤖 Assistant: Excellent! Can you share 2-3 key achievements or projects you're proud of?
👤 User: Built a recommendation system, led a team of 5 devs
🤖 Assistant: Perfect! What tone would you like - professional, casual, or creative?
👤 User: Professional
🤖 Assistant: Here's your professional bio:
[Generated Bio Content]
Would you like me to regenerate it, or shall we work on something else?
Key Features of Chat Interface ✅ Natural conversation - feels like chatting with a human assistant ✅ Context-aware - remembers what user said earlier ✅ Guided questions - bot asks for missing information ✅ Quick actions - buttons to jump to specific features ✅ Copy & export - easy to save generated content ✅ Regenerate option - can refine outputs ✅ Conversation history - see past chats in sidebar
Daily Coordination Day 2 Evening: Dev 3 shares conversation scripts with Dev 1 Day 3 Morning: Dev 1 confirms chat API ready for Dev 2 Day 3 Afternoon: All devs test conversation flows together Day 4 Morning: Team reviews UX and makes improvements
This chat-based approach makes the app more engaging and user-friendly! 🚀